Welcome to the CBMML website!

Recent clinical studies have reported that the pre-existence of unnoticed silent myocardial infarction (SMI) in patients hospitalized with acute myocardial infarction (AMI) significantly worsens morbidity and increases mortality. SMI patients exhibit infarcts of different sizes and locations. This condition occurs in conjunction with left ventricular (LV) hypertrophy. The distinct roles of these abnormalities on LV functions and their contribution to AMI prognosis are poorly understood. To address these gaps, this study utilizes a coupled finite element (FE) framework to investigate the effect of the size and location of isolated SMI and AMI on LV performance. Furthermore, the influence of the simultaneous occurrence of SMI and hypertrophy alongside AMI is evaluated. The results show that under the simulation conditions, the peak global longitudinal strain is influenced by the variation in the location and size of the SMI and AMI. However, ejection fraction (EF), end-diastolic pressure (EDP), and peak global circumferential strain are influenced by the size of the SMI. The findings indicate that the presence of pre-existing SMI and hypertrophy will notably impair the EF and global circumferential strain, resulting in worse morbidity in an AMI patient.

Phase change characteristics of refrigerant blends is essential due to their wide applications and environmental relevance. This work investigates nanoscale boiling in R152a/R1234ze(E) blends using non-equilibrium molecular dynamics (NEMD) simulations under controlled heating (80–200 K/ns). Five compositions (0 %, 33 %, 50 %, 67 %, and 100 % R152a) are analyzed in a three-phase domain comprising liquid and vapor over a platinum wall with linearly increasing temperature to induce necessary phase change. Key characteristics—atomic kinetics, net evaporation, wall heat flux, bubble nucleation/growth, and near-wall temperature—are examined across blend ratios and heating conditions. Increasing R152a enhances boiling performance with a significant change in boiling mode. Significant enhancement in net evaporation number, bubble volume growth rate and time-average heat flux is noticed with the increase in R152a for all heating rates. However, blend of 67 % R152a demonstrates thermal performance comparable to pure R152a at low as well as high heating rates, but lags at moderate rates. Interfacial analysis shows the interfacial thermal resistance of R1234ze(E) is approximately 34 % lower than that of R152a although the bulk thermal resistance of R1234ze(E) is higher. Moreover, increase in R152a in the refrigerant blend enhanced its interfacial thermal resistance. This contrast enables optimal heat transfer in mixed compositions. Specifically, the 67 % R152a blend benefits from favorable molecular distribution, balancing interfacial and bulk transport properties for improved phase change behavior. These findings provide insights into tuning refrigerant blends for efficient heat transfer in nanoscale boiling systems.

Recent clinical studies have reported that heart failure with preserved ejection fraction (HFpEF) can be divided into two phenotypes based on the range of ejection fraction (EF), namely HFpEF with higher EF and HFpEF with lower EF. These phenotypes exhibit distinct left ventricle (LV) remodelling patterns and dynamics. However, the influence of LV remodelling on various LV functional indices and the underlying mechanics for these two phenotypes are not well understood. To address these issues, this study employs a coupled finite element analysis (FEA) framework to analyse the impact of various ventricular remodelling patterns, specifically concentric remodelling (CR), concentric hypertrophy (CH), and eccentric hypertrophy (EH), with and without LV wall thickening on LV functional indices. Further, the geometries with a moderate level of remodelling from each pattern are subjected to fibre stiffening and contractile impairment to examine their effect in replicating the different features of HFpEF. The results show that with severe CR, LV could exhibit the characteristics of HFpEF with higher EF, as observed in recent clinical studies. Controlled fibre stiffening can simultaneously increase the end-diastolic pressure (EDP) and reduce the peak longitudinal strain (ell) without significant reduction in EF, facilitating the moderate CR geometries to fit into this phenotype. Similarly, fibre stiffening can assist the CH and ‘EH with wall thickening’ cases to replicate HFpEF with lower EF. These findings suggest that potential treatment for these two phenotypes should target the bio-origins of their distinct ventricular remodelling patterns and the extent of myocardial stiffening.

Pulmonary arterial hypertension (PAH) is a complex disease involving increased resistance in the pulmonary arteries and subsequent right ventricular (RV) remodeling. Ventricular-arterial interactions are fundamental to PAH pathophysiology but are rarely captured in computational models. It is important to identify metrics that capture and quantify these interactions to inform our understanding of this disease as well as potentially facilitate patient stratification. Towards this end, we developed and calibrated two multi-scale high-resolution closed-loop computational models using open-source software: a high-resolution arterial model implemented using CRIMSON, and a high-resolution ventricular model implemented using FEniCS. Models were constructed with clinical data including non-invasive imaging and invasive hemodynamic measurements from a cohort of pediatric PAH patients. A contribution of this work is the discussion of inconsistencies in anatomical and hemodynamic data routinely acquired in PAH patients. We proposed and implemented strategies to mitigate these inconsistencies, and subsequently use this data to inform and calibrate computational models of the ventricles and large arteries. Computational models based on adjusted clinical data were calibrated until the simulated results for the high-resolution arterial models matched within 10% of adjusted data consisting of pressure and flow, whereas the high-resolution ventricular models were calibrated until simulation results matched adjusted data of volume and pressure waveforms within 10%. A statistical analysis was performed to correlate numerous data-derived and model-derived metrics with clinically assessed disease severity. Several model-derived metrics were strongly correlated with clinically assessed disease severity, suggesting that computational models may aid in assessing PAH severity.